AIM Score vs. Gene Expression
Full X range:
Auto X range:
Group Comparisons: Boxplots
CP73
Model Comparison: AIM ~ expression + C(dose) vs AIM ~ C(dose)
| F-statistic | p-value | df difference |
| 0.724 | 0.405 | 1.0 |
Model:
AIM ~ expression + C(dose) + expression:C(dose)
OLS Regression Results
| Dep. Variable: | AIM | R-squared: | 0.723 |
| Model: | OLS | Adj. R-squared: | 0.680 |
| Method: | Least Squares | F-statistic: | 16.55 |
| Date: | Mon, 27 Jan 2025 | Prob (F-statistic): | 1.57e-05 |
| Time: | 21:50:31 | Log-Likelihood: | -98.330 |
| No. Observations: | 23 | AIC: | 204.7 |
| Df Residuals: | 19 | BIC: | 209.2 |
| Df Model: | 3 | | |
| coef | std err | t | P>|t| | [95.0% Conf. Int.] |
| Intercept | -33.2065 | 87.472 | -0.380 | 0.708 | -216.287 149.874 |
| C(dose)[T.1] | 280.3230 | 111.547 | 2.513 | 0.021 | 46.853 513.793 |
| expression | 18.0122 | 17.988 | 1.001 | 0.329 | -19.637 55.661 |
| expression:C(dose)[T.1] | -48.2220 | 23.377 | -2.063 | 0.053 | -97.150 0.706 |
| Omnibus: | 1.557 | Durbin-Watson: | 1.708 |
| Prob(Omnibus): | 0.459 | Jarque-Bera (JB): | 1.226 |
| Skew: | 0.365 | Prob(JB): | 0.542 |
| Kurtosis: | 2.135 | Cond. No. | 187. |
Model:
AIM ~ expression + C(dose)
OLS Regression Results
| Dep. Variable: | AIM | R-squared: | 0.661 |
| Model: | OLS | Adj. R-squared: | 0.627 |
| Method: | Least Squares | F-statistic: | 19.53 |
| Date: | Mon, 27 Jan 2025 | Prob (F-statistic): | 1.99e-05 |
| Time: | 21:50:31 | Log-Likelihood: | -100.65 |
| No. Observations: | 23 | AIC: | 207.3 |
| Df Residuals: | 20 | BIC: | 210.7 |
| Df Model: | 2 | | |
| coef | std err | t | P>|t| | [95.0% Conf. Int.] |
| Intercept | 105.3583 | 60.415 | 1.744 | 0.097 | -20.666 231.382 |
| C(dose)[T.1] | 50.8812 | 9.086 | 5.600 | 0.000 | 31.928 69.834 |
| expression | -10.5397 | 12.388 | -0.851 | 0.405 | -36.381 15.302 |
| Omnibus: | 2.151 | Durbin-Watson: | 1.858 |
| Prob(Omnibus): | 0.341 | Jarque-Bera (JB): | 1.175 |
| Skew: | 0.174 | Prob(JB): | 0.556 |
| Kurtosis: | 1.949 | Cond. No. | 70.1 |
Model:
AIM ~ C(dose)
OLS Regression Results
| Dep. Variable: | AIM | R-squared: | 0.649 |
| Model: | OLS | Adj. R-squared: | 0.632 |
| Method: | Least Squares | F-statistic: | 38.84 |
| Date: | Mon, 27 Jan 2025 | Prob (F-statistic): | 3.51e-06 |
| Time: | 21:50:31 | Log-Likelihood: | -101.06 |
| No. Observations: | 23 | AIC: | 206.1 |
| Df Residuals: | 21 | BIC: | 208.4 |
| Df Model: | 1 | | |
| coef | std err | t | P>|t| | [95.0% Conf. Int.] |
| Intercept | 54.2083 | 5.919 | 9.159 | 0.000 | 41.900 66.517 |
| C(dose)[T.1] | 53.3371 | 8.558 | 6.232 | 0.000 | 35.539 71.135 |
| Omnibus: | 0.322 | Durbin-Watson: | 1.888 |
| Prob(Omnibus): | 0.851 | Jarque-Bera (JB): | 0.485 |
| Skew: | 0.060 | Prob(JB): | 0.785 |
| Kurtosis: | 2.299 | Cond. No. | 2.57 |
Model:
AIM ~ expression
OLS Regression Results
| Dep. Variable: | AIM | R-squared: | 0.130 |
| Model: | OLS | Adj. R-squared: | 0.089 |
| Method: | Least Squares | F-statistic: | 3.146 |
| Date: | Mon, 27 Jan 2025 | Prob (F-statistic): | 0.0906 |
| Time: | 21:50:31 | Log-Likelihood: | -111.50 |
| No. Observations: | 23 | AIC: | 227.0 |
| Df Residuals: | 21 | BIC: | 229.3 |
| Df Model: | 1 | | |
| coef | std err | t | P>|t| | [95.0% Conf. Int.] |
| Intercept | 234.1984 | 87.362 | 2.681 | 0.014 | 52.520 415.877 |
| expression | -32.5797 | 18.370 | -1.774 | 0.091 | -70.781 5.622 |
| Omnibus: | 1.277 | Durbin-Watson: | 2.324 |
| Prob(Omnibus): | 0.528 | Jarque-Bera (JB): | 0.867 |
| Skew: | -0.005 | Prob(JB): | 0.648 |
| Kurtosis: | 2.049 | Cond. No. | 64.4 |
CP101
Model Comparison: AIM ~ expression + C(dose) vs AIM ~ C(dose)
| F-statistic | p-value | df difference |
| 1.136 | 0.308 | 1.0 |
Model:
AIM ~ expression + C(dose) + expression:C(dose)
OLS Regression Results
| Dep. Variable: | AIM | R-squared: | 0.527 |
| Model: | OLS | Adj. R-squared: | 0.398 |
| Method: | Least Squares | F-statistic: | 4.082 |
| Date: | Mon, 27 Jan 2025 | Prob (F-statistic): | 0.0356 |
| Time: | 21:50:31 | Log-Likelihood: | -69.689 |
| No. Observations: | 15 | AIC: | 147.4 |
| Df Residuals: | 11 | BIC: | 150.2 |
| Df Model: | 3 | | |
| coef | std err | t | P>|t| | [95.0% Conf. Int.] |
| Intercept | 102.2711 | 143.249 | 0.714 | 0.490 | -213.019 417.561 |
| C(dose)[T.1] | 226.1313 | 214.956 | 1.052 | 0.315 | -246.983 699.246 |
| expression | -6.6158 | 27.118 | -0.244 | 0.812 | -66.301 53.070 |
| expression:C(dose)[T.1] | -34.7259 | 41.353 | -0.840 | 0.419 | -125.743 56.292 |
| Omnibus: | 0.106 | Durbin-Watson: | 1.239 |
| Prob(Omnibus): | 0.948 | Jarque-Bera (JB): | 0.057 |
| Skew: | -0.012 | Prob(JB): | 0.972 |
| Kurtosis: | 2.698 | Cond. No. | 197. |
Model:
AIM ~ expression + C(dose)
OLS Regression Results
| Dep. Variable: | AIM | R-squared: | 0.496 |
| Model: | OLS | Adj. R-squared: | 0.413 |
| Method: | Least Squares | F-statistic: | 5.915 |
| Date: | Mon, 27 Jan 2025 | Prob (F-statistic): | 0.0163 |
| Time: | 21:50:31 | Log-Likelihood: | -70.155 |
| No. Observations: | 15 | AIC: | 146.3 |
| Df Residuals: | 12 | BIC: | 148.4 |
| Df Model: | 2 | | |
| coef | std err | t | P>|t| | [95.0% Conf. Int.] |
| Intercept | 180.9160 | 107.055 | 1.690 | 0.117 | -52.336 414.168 |
| C(dose)[T.1] | 46.0946 | 15.323 | 3.008 | 0.011 | 12.709 79.480 |
| expression | -21.5487 | 20.220 | -1.066 | 0.308 | -65.604 22.507 |
| Omnibus: | 0.580 | Durbin-Watson: | 1.119 |
| Prob(Omnibus): | 0.748 | Jarque-Bera (JB): | 0.590 |
| Skew: | -0.371 | Prob(JB): | 0.745 |
| Kurtosis: | 2.373 | Cond. No. | 77.3 |
Model:
AIM ~ C(dose)
OLS Regression Results
| Dep. Variable: | AIM | R-squared: | 0.449 |
| Model: | OLS | Adj. R-squared: | 0.406 |
| Method: | Least Squares | F-statistic: | 10.58 |
| Date: | Mon, 27 Jan 2025 | Prob (F-statistic): | 0.00629 |
| Time: | 21:50:31 | Log-Likelihood: | -70.833 |
| No. Observations: | 15 | AIC: | 145.7 |
| Df Residuals: | 13 | BIC: | 147.1 |
| Df Model: | 1 | | |
| coef | std err | t | P>|t| | [95.0% Conf. Int.] |
| Intercept | 67.4286 | 11.044 | 6.106 | 0.000 | 43.570 91.287 |
| C(dose)[T.1] | 49.1964 | 15.122 | 3.253 | 0.006 | 16.527 81.866 |
| Omnibus: | 2.713 | Durbin-Watson: | 0.810 |
| Prob(Omnibus): | 0.258 | Jarque-Bera (JB): | 1.868 |
| Skew: | -0.843 | Prob(JB): | 0.393 |
| Kurtosis: | 2.619 | Cond. No. | 2.70 |
Model:
AIM ~ expression
OLS Regression Results
| Dep. Variable: | AIM | R-squared: | 0.117 |
| Model: | OLS | Adj. R-squared: | 0.049 |
| Method: | Least Squares | F-statistic: | 1.717 |
| Date: | Mon, 27 Jan 2025 | Prob (F-statistic): | 0.213 |
| Time: | 21:50:31 | Log-Likelihood: | -74.370 |
| No. Observations: | 15 | AIC: | 152.7 |
| Df Residuals: | 13 | BIC: | 154.2 |
| Df Model: | 1 | | |
| coef | std err | t | P>|t| | [95.0% Conf. Int.] |
| Intercept | 265.4627 | 131.446 | 2.020 | 0.065 | -18.509 549.435 |
| expression | -33.1028 | 25.261 | -1.310 | 0.213 | -87.676 21.470 |
| Omnibus: | 0.184 | Durbin-Watson: | 1.540 |
| Prob(Omnibus): | 0.912 | Jarque-Bera (JB): | 0.305 |
| Skew: | 0.211 | Prob(JB): | 0.859 |
| Kurtosis: | 2.444 | Cond. No. | 74.3 |